Probing protein-tannin interactions by isothermal titration microcalorimetry

Isothermal titration microcalorimetry (ITC) has been applied to investigate protein-tannin interactions. Two hydrolyzable tannins were studied, namely myrabolan and tara tannins, for their interaction with bovine serum albumin (BSA), a model globular protein, and gelatin, a model proline-rich random coil protein. Calorimetry data indicate that protein-tannin interaction mechanisms are dependent upon the nature of the protein involved. Tannins apparently interact nonspecifically with the globular BSA, leading to binding saturation at estimated tannin/BSA molar ratios of 48:1 for tara- and 178:1 for myrabolan tannins. Tannins bind to the random coil protein gelatin by a two-stage mechanism. The energetics of the first stage show evidence for cooperative binding of tannins to the protein, while the second stage indicates gradual saturation of binding sites as observed for interaction with BSA. The structure and flexibility of the tannins themselves alters the stoichiometry of the interaction, but does not appear to have any significant affect on the overall binding mechanism observed. This study demonstrates the potential of ITC for providing an insight into the nature of protein-tannin interactions.

Probing the receptor interactions of an H5 avian influenza virus using a baculovirus expression system and functionalised poly(acrylic acid) ligands

Influenza viruses attach to host cells by binding to terminal sialic acid (Neu5Ac) on glycoproteins or glycolipids. Both the linkage of Neu5Ac and the identity of other carbohydrates within the oligosaccharide are thought to play roles in restricting the host range of the virus. In this study, the receptor specificity of an H5 avian influenza virus haemagglutinin protein that has recently infected man (influenza strain A/Vietnam/1194/04) has been probed using carbohydrate functionalised poly(acrylic acid) polymers. A baculovirus expression system that allows facile and safe analysis of the Neu5Ac binding specificity of mutants of H5 HA engineered at sites that are predicted to effect a switch in host range has also been developed. (C) 2007 Elsevier Ltd. All rights reserved.

A combined Bayesian Markovian approach for behaviour recognition

Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although these techniques are extremely powerful and well developed, both have important limitations. By fusing these techniques together to form Bayes-Markov chains, the advantages of both techniques can be preserved, while reducing their limitations. The Bayes-Markov technique forms the basis of a common, flexible framework for supplementing Markov chains with additional features. This results in improved user output, and aids in the rapid development of flexible and efficient behaviour recognition systems.

Probing a biomimetic approach to Mycaperoxide B: hydroperoxidation studies

Hydroperoxidation studies on a series of alkene substrates demonstrate the introduction of the hydroperoxide functional group into the required position for a biosynthetically inspired synthesis of mycaperoxide B.

Probing the effect of allylic substitution on cyclic ammonium ylid rearrangements

The [2,3]-sigmatropic rearrangement of tetrahydropyridine-derived ammonium ylids is a valuable method for the preparation of substituted pyrrolidine carboxylates. The presence of an allylic substituent does not intrinsically reduce the yield of rearrangements, and the diastereoselectivity of rearrangement is related to the structure of the diazo reactant. The method represents a very rapid means of accessing complex pyrrolidines, as shown by preparation of a precursor to the core of lactacystin.

Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations

A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.

An analysis of the impact of R&D on productivity using Bayesian model averaging with a reversible jump algorithm.

A Bayesian Model Averaging approach to the estimation of lag structures is introduced, and applied to assess the impact of R&D on agricultural productivity in the US from 1889 to 1990. Lag and structural break coefficients are estimated using a reversible jump algorithm that traverses the model space. In addition to producing estimates and standard deviations for the coe¢ cients, the probability that a given lag (or break) enters the model is estimated. The approach is extended to select models populated with Gamma distributed lags of di¤erent frequencies. Results are consistent with the hypothesis that R&D positively drives productivity. Gamma lags are found to retain their usefulness in imposing a plausible structure on lag coe¢ cients, and their role is enhanced through the use of model averaging.

Bayesian model averaging and identification of structural breaks in time series

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

Farm forestry in Pakistan: an application of Theory of Planned Behaviour by probing into the measurement issues

A research has been conducted over methodological issues concerning the Theory of Planned Behaviour (TPB) by determining an appropriate measurement (direct and indirect) of constructs and selection of a plausible scaling techniques (unipolar and bipolar) of constructs: attitude, subjective norm, perceived behavioural control and intention that are important in explaining farm level tree planting in Pakistan. Unipolar scoring of beliefs showed higher correlation among the constructs of TPB than bipolar scaling technique. Both direct and indirect methods yielded significant results in explaining intention to perform farm forestry except the belief based measure of perceived behavioural control, which were analysed as statistically non-significant. A need to examine more carefully the scoring of perceived behavioural control (PBC) has been expressed